Globally convergent modified Perry’s conjugate gradient method
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摘要
Conjugate gradient methods are probably the most famous iterative methods for solving large scale optimization problems in scientific and engineering computation, characterized by the simplicity of their iteration and their low memory requirements. In this paper, we propose a new conjugate gradient method which is based on the MBFGS secant condition by modifying Perry’s method. Our proposed method ensures sufficient descent independent of the accuracy of the line search and it is globally convergent under some assumptions. Numerical experiments are also presented.
论文关键词:Unconstrained optimization,Conjugate gradient method,Sufficient descent property,Line search,Global convergence
论文评审过程:Available online 21 March 2012.
论文官网地址:https://doi.org/10.1016/j.amc.2012.02.076